There has been a requirement for a technique to separate an input image into a specular reflection component and a diffuse reflection component. For example, in the field of object recognition with a robot vision, a technique has been studied which enhances the recognition accuracy by acquiring the reflection characteristics of an object's glossy surface. In contrast, there is a technique in which pixels are extracted by means of the hue of an object in an image, and a diffuse reflection factor, which describes the actual color component of the surface, is estimated from the extracted pixels. There is disclosed a technique in which, by using the estimated diffuse reflection factor to separate the color that is changeable by the illumination, the diffuse reflection component and specular reflection component of the target pixel are separated from each other. However, in a case where a noise is added to the pixel value of the processing target pixel, the hue of the observed pixel may greatly deviate from its true value. For this reason, in a case of Non-patent reference, mentioned below, in which a fixed threshold is used to distinguish hues from one another, deterioration occurs in the accuracy of the extraction of a pixel which is included in a surface having the same diffuse reflection factor as the processing target pixel. Such deterioration eventually deteriorates the accuracy of the separation of the diffuse reflection component.
The related art of contents of which are incorporated herein by reference, which are described in Higo et al. (2006), “Realtime Removal of Specular Reflection Component Based on Dichromatic Reflection Model,” Information Society of Japan—Computer Vision and Image Media (CVIM), pp. 211-218.